#PACOTES
#install.packages("psych")
#install.packages("chisq.posthoc.test")
#install.packages("summarytools")
library(psych)
## Warning: package 'psych' was built under R version 4.0.5
library(chisq.posthoc.test)
#dados_videos <- read.csv("dados_aline.csv")
dados_videos <- read.csv("banco_aline_quanti_99.csv")
describe(dados_videos)
summary(dados_videos)
## Carimbo.de.data.hora ID q1 q2
## Length:99 Length:99 Min. :2.00 Min. :1.000
## Class :character Class :character 1st Qu.:3.00 1st Qu.:2.000
## Mode :character Mode :character Median :4.00 Median :2.000
## Mean :3.96 Mean :2.232
## 3rd Qu.:5.00 3rd Qu.:3.000
## Max. :6.00 Max. :4.000
## q3 q4 q5 q6
## Min. :1.000 Min. : 1456 Min. : 35.0 Min. : 0.0
## 1st Qu.:2.000 1st Qu.: 2164 1st Qu.: 285.0 1st Qu.: 54.5
## Median :2.000 Median : 5326 Median : 487.0 Median : 156.0
## Mean :2.242 Mean : 22432 Mean : 736.3 Mean : 1100.0
## 3rd Qu.:3.000 3rd Qu.: 13791 3rd Qu.: 797.0 3rd Qu.: 578.5
## Max. :3.000 Max. :613011 Max. :3717.0 Max. :22000.0
## q7 q9 q10 q11
## Min. : 0.00 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.: 1.00 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median : 4.00 Median :1.000 Median :2.000 Median :2.000
## Mean : 27.41 Mean :1.071 Mean :1.586 Mean :1.566
## 3rd Qu.: 11.00 3rd Qu.:1.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :1400.00 Max. :2.000 Max. :2.000 Max. :2.000
## q12 q13 q14 q15
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :1.000 Median :2.000 Median :1.000
## Mean :1.717 Mean :1.495 Mean :1.556 Mean :1.273
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q16 q17 q18 q19
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :1.000 Median :1.000 Median :2.000 Median :1.000
## Mean :1.444 Mean :1.101 Mean :1.667 Mean :1.424
## 3rd Qu.:2.000 3rd Qu.:1.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q20 q21 q22 q23
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :1.737 Mean :1.636 Mean :1.616 Mean :1.586
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q24 q25 q26 q27
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:2.000
## Median :2.000 Median :1.000 Median :2.000 Median :2.000
## Mean :1.566 Mean :1.333 Mean :1.717 Mean :1.899
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q28 q29 q30 q31
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.500 1st Qu.:2.000 1st Qu.:2.000
## Median :2.000 Median :2.000 Median :2.000 Median :2.000
## Mean :1.687 Mean :1.747 Mean :1.838 Mean :1.859
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q32 q33 q34 q35
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:1.000
## Median :2.000 Median :1.000 Median :2.000 Median :2.000
## Mean :1.667 Mean :1.434 Mean :1.545 Mean :1.657
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q36 q37 q38 q39
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:1.000 1st Qu.:2.000
## Median :2.000 Median :1.000 Median :2.000 Median :2.000
## Mean :1.808 Mean :1.384 Mean :1.646 Mean :1.919
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000 Max. :2.000 Max. :2.000
## q40 q41
## Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000
## Median :2.000 Median :2.000
## Mean :1.939 Mean :1.626
## 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :2.000 Max. :2.000
table<-with(dados_videos,table(q9,q3))
table
## q3
## q9 1 2 3
## 1 17 34 41
## 2 3 1 3
prop.table(table)
## q3
## q9 1 2 3
## 1 0.17171717 0.34343434 0.41414141
## 2 0.03030303 0.01010101 0.03030303
chisq.test(dados_videos$q9, dados_videos$q3)
## Warning in chisq.test(dados_videos$q9, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q9 and dados_videos$q3
## X-squared = 2.8637, df = 2, p-value = 0.2389
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
sig<-.05
sigAdj<-sig/(nrow(table)*ncol(table))
sigAdj
## [1] 0.008333333
qnorm(sigAdj/2)
## [1] -2.638257
table<-with(dados_videos,table(q10,q3))
table
## q3
## q10 1 2 3
## 1 18 5 18
## 2 2 30 26
prop.table(table)
## q3
## q10 1 2 3
## 1 0.18181818 0.05050505 0.18181818
## 2 0.02020202 0.30303030 0.26262626
chisq.test(dados_videos$q10, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q10 and dados_videos$q3
## X-squared = 30.079, df = 2, p-value = 2.94e-07
chisq.posthoc.test(table)
table<-with(dados_videos,table(q11,q3))
table
## q3
## q11 1 2 3
## 1 3 11 29
## 2 17 24 15
prop.table(table)
## q3
## q11 1 2 3
## 1 0.03030303 0.11111111 0.29292929
## 2 0.17171717 0.24242424 0.15151515
chisq.test(dados_videos$q11, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q11 and dados_videos$q3
## X-squared = 17.681, df = 2, p-value = 0.0001448
chisq.posthoc.test(table)
table<-with(dados_videos,table(q12,q3))
table
## q3
## q12 1 2 3
## 1 3 10 15
## 2 17 25 29
prop.table(table)
## q3
## q12 1 2 3
## 1 0.03030303 0.10101010 0.15151515
## 2 0.17171717 0.25252525 0.29292929
chisq.test(dados_videos$q12, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q12 and dados_videos$q3
## X-squared = 2.4729, df = 2, p-value = 0.2904
chisq.posthoc.test(table)
table<-with(dados_videos,table(q13,q3))
table
## q3
## q13 1 2 3
## 1 10 16 24
## 2 10 19 20
prop.table(table)
## q3
## q13 1 2 3
## 1 0.1010101 0.1616162 0.2424242
## 2 0.1010101 0.1919192 0.2020202
chisq.test(dados_videos$q13, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q13 and dados_videos$q3
## X-squared = 0.61074, df = 2, p-value = 0.7369
chisq.posthoc.test(table)
table<-with(dados_videos,table(q14,q3))
table
## q3
## q14 1 2 3
## 1 8 11 25
## 2 12 24 19
prop.table(table)
## q3
## q14 1 2 3
## 1 0.08080808 0.11111111 0.25252525
## 2 0.12121212 0.24242424 0.19191919
chisq.test(dados_videos$q14, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q14 and dados_videos$q3
## X-squared = 5.2898, df = 2, p-value = 0.07101
chisq.posthoc.test(table)
table<-with(dados_videos,table(q15,q3))
table
## q3
## q15 1 2 3
## 1 13 24 35
## 2 7 11 9
prop.table(table)
## q3
## q15 1 2 3
## 1 0.13131313 0.24242424 0.35353535
## 2 0.07070707 0.11111111 0.09090909
chisq.test(dados_videos$q15, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q15 and dados_videos$q3
## X-squared = 1.9381, df = 2, p-value = 0.3794
chisq.posthoc.test(table)
table<-with(dados_videos,table(q16,q3))
table
## q3
## q16 1 2 3
## 1 5 21 29
## 2 15 14 15
prop.table(table)
## q3
## q16 1 2 3
## 1 0.05050505 0.21212121 0.29292929
## 2 0.15151515 0.14141414 0.15151515
chisq.test(dados_videos$q16, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q16 and dados_videos$q3
## X-squared = 9.7527, df = 2, p-value = 0.007625
chisq.posthoc.test(table)
#Menciona o glúten como a causa primária de DC
table<-with(dados_videos,table(q17,q3))
table
## q3
## q17 1 2 3
## 1 17 30 42
## 2 3 5 2
prop.table(table)
## q3
## q17 1 2 3
## 1 0.17171717 0.30303030 0.42424242
## 2 0.03030303 0.05050505 0.02020202
chisq.test(dados_videos$q17, dados_videos$q3)
## Warning in chisq.test(dados_videos$q17, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q17 and dados_videos$q3
## X-squared = 2.6991, df = 2, p-value = 0.2594
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q18,q3))
table
## q3
## q18 1 2 3
## 1 3 7 23
## 2 17 28 21
prop.table(table)
## q3
## q18 1 2 3
## 1 0.03030303 0.07070707 0.23232323
## 2 0.17171717 0.28282828 0.21212121
chisq.test(dados_videos$q18, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q18 and dados_videos$q3
## X-squared = 12.927, df = 2, p-value = 0.001559
chisq.posthoc.test(table)
#Menciona o risco para o desenvolvimento de outras condições crônicas de saúde
table<-with(dados_videos,table(q19,q3))
table
## q3
## q19 1 2 3
## 1 11 17 29
## 2 9 18 15
prop.table(table)
## q3
## q19 1 2 3
## 1 0.11111111 0.17171717 0.29292929
## 2 0.09090909 0.18181818 0.15151515
chisq.test(dados_videos$q19, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q19 and dados_videos$q3
## X-squared = 2.467, df = 2, p-value = 0.2913
chisq.posthoc.test(table)
table<-with(dados_videos,table(q20,q3))
table
## q3
## q20 1 2 3
## 1 5 9 12
## 2 15 26 32
prop.table(table)
## q3
## q20 1 2 3
## 1 0.05050505 0.09090909 0.12121212
## 2 0.15151515 0.26262626 0.32323232
chisq.test(dados_videos$q20, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q20 and dados_videos$q3
## X-squared = 0.045081, df = 2, p-value = 0.9777
chisq.posthoc.test(table)
table<-with(dados_videos,table(q21,q3))
table
## q3
## q21 1 2 3
## 1 11 8 17
## 2 9 27 27
prop.table(table)
## q3
## q21 1 2 3
## 1 0.11111111 0.08080808 0.17171717
## 2 0.09090909 0.27272727 0.27272727
chisq.test(dados_videos$q21, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q21 and dados_videos$q3
## X-squared = 5.8592, df = 2, p-value = 0.05342
chisq.posthoc.test(table)
#Menciona alterações na qualidade de vida
table<-with(dados_videos,table(q22,q3))
table
## q3
## q22 1 2 3
## 1 11 9 18
## 2 9 26 26
prop.table(table)
## q3
## q22 1 2 3
## 1 0.11111111 0.09090909 0.18181818
## 2 0.09090909 0.26262626 0.26262626
chisq.test(dados_videos$q22, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q22 and dados_videos$q3
## X-squared = 4.8289, df = 2, p-value = 0.08942
chisq.posthoc.test(table)
table<-with(dados_videos,table(q23,q3))
table
## q3
## q23 1 2 3
## 1 4 15 22
## 2 16 20 22
prop.table(table)
## q3
## q23 1 2 3
## 1 0.04040404 0.15151515 0.22222222
## 2 0.16161616 0.20202020 0.22222222
chisq.test(dados_videos$q23, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q23 and dados_videos$q3
## X-squared = 5.1469, df = 2, p-value = 0.07627
chisq.posthoc.test(table)
table<-with(dados_videos,table(q24,q3))
table
## q3
## q24 1 2 3
## 1 7 14 22
## 2 13 21 22
prop.table(table)
## q3
## q24 1 2 3
## 1 0.07070707 0.14141414 0.22222222
## 2 0.13131313 0.21212121 0.22222222
chisq.test(dados_videos$q24, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q24 and dados_videos$q3
## X-squared = 1.5191, df = 2, p-value = 0.4679
chisq.posthoc.test(table)
table<-with(dados_videos,table(q25,q3))
table
## q3
## q25 1 2 3
## 1 11 20 35
## 2 9 15 9
prop.table(table)
## q3
## q25 1 2 3
## 1 0.11111111 0.20202020 0.35353535
## 2 0.09090909 0.15151515 0.09090909
chisq.test(dados_videos$q25, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q25 and dados_videos$q3
## X-squared = 5.9377, df = 2, p-value = 0.05136
chisq.posthoc.test(table)
table<-with(dados_videos,table(q26,q3))
table
## q3
## q26 1 2 3
## 1 5 8 15
## 2 15 27 29
prop.table(table)
## q3
## q26 1 2 3
## 1 0.05050505 0.08080808 0.15151515
## 2 0.15151515 0.27272727 0.29292929
chisq.test(dados_videos$q26, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q26 and dados_videos$q3
## X-squared = 1.346, df = 2, p-value = 0.5102
chisq.posthoc.test(table)
table<-with(dados_videos,table(q27,q3))
table
## q3
## q27 1 2 3
## 1 1 1 8
## 2 19 34 36
prop.table(table)
## q3
## q27 1 2 3
## 1 0.01010101 0.01010101 0.08080808
## 2 0.19191919 0.34343434 0.36363636
chisq.test(dados_videos$q27, dados_videos$q3)
## Warning in chisq.test(dados_videos$q27, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q27 and dados_videos$q3
## X-squared = 5.7596, df = 2, p-value = 0.05614
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q28,q3))
table
## q3
## q28 1 2 3
## 1 8 5 18
## 2 12 30 26
prop.table(table)
## q3
## q28 1 2 3
## 1 0.08080808 0.05050505 0.18181818
## 2 0.12121212 0.30303030 0.26262626
chisq.test(dados_videos$q28, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q28 and dados_videos$q3
## X-squared = 7.3036, df = 2, p-value = 0.02594
chisq.posthoc.test(table)
table<-with(dados_videos,table(q29,q3))
table
## q3
## q29 1 2 3
## 1 5 6 14
## 2 15 29 30
prop.table(table)
## q3
## q29 1 2 3
## 1 0.05050505 0.06060606 0.14141414
## 2 0.15151515 0.29292929 0.30303030
chisq.test(dados_videos$q29, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q29 and dados_videos$q3
## X-squared = 2.225, df = 2, p-value = 0.3287
chisq.posthoc.test(table)
table<-with(dados_videos,table(q30,q3))
table
## q3
## q30 1 2 3
## 1 3 7 6
## 2 17 28 38
prop.table(table)
## q3
## q30 1 2 3
## 1 0.03030303 0.07070707 0.06060606
## 2 0.17171717 0.28282828 0.38383838
chisq.test(dados_videos$q30, dados_videos$q3)
## Warning in chisq.test(dados_videos$q30, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q30 and dados_videos$q3
## X-squared = 0.60757, df = 2, p-value = 0.738
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q31,q3))
table
## q3
## q31 1 2 3
## 1 2 3 9
## 2 18 32 35
prop.table(table)
## q3
## q31 1 2 3
## 1 0.02020202 0.03030303 0.09090909
## 2 0.18181818 0.32323232 0.35353535
chisq.test(dados_videos$q31, dados_videos$q3)
## Warning in chisq.test(dados_videos$q31, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q31 and dados_videos$q3
## X-squared = 2.6212, df = 2, p-value = 0.2697
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q32,q3))
table
## q3
## q32 1 2 3
## 1 6 11 16
## 2 14 24 28
prop.table(table)
## q3
## q32 1 2 3
## 1 0.06060606 0.11111111 0.16161616
## 2 0.14141414 0.24242424 0.28282828
chisq.test(dados_videos$q32, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q32 and dados_videos$q3
## X-squared = 0.33896, df = 2, p-value = 0.8441
chisq.posthoc.test(table)
table<-with(dados_videos,table(q33,q3))
table
## q3
## q33 1 2 3
## 1 10 17 29
## 2 10 18 15
prop.table(table)
## q3
## q33 1 2 3
## 1 0.1010101 0.1717172 0.2929293
## 2 0.1010101 0.1818182 0.1515152
chisq.test(dados_videos$q33, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q33 and dados_videos$q3
## X-squared = 2.8248, df = 2, p-value = 0.2436
chisq.posthoc.test(table)
table<-with(dados_videos,table(q34,q3))
table
## q3
## q34 1 2 3
## 1 6 14 25
## 2 14 21 19
prop.table(table)
## q3
## q34 1 2 3
## 1 0.06060606 0.14141414 0.25252525
## 2 0.14141414 0.21212121 0.19191919
chisq.test(dados_videos$q34, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q34 and dados_videos$q3
## X-squared = 4.6383, df = 2, p-value = 0.09836
chisq.posthoc.test(table)
table<-with(dados_videos,table(q35,q3))
table
## q3
## q35 1 2 3
## 1 6 12 16
## 2 14 23 28
prop.table(table)
## q3
## q35 1 2 3
## 1 0.06060606 0.12121212 0.16161616
## 2 0.14141414 0.23232323 0.28282828
chisq.test(dados_videos$q35, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q35 and dados_videos$q3
## X-squared = 0.24702, df = 2, p-value = 0.8838
chisq.posthoc.test(table)
table<-with(dados_videos,table(q36,q3))
table
## q3
## q36 1 2 3
## 1 4 3 12
## 2 16 32 32
prop.table(table)
## q3
## q36 1 2 3
## 1 0.04040404 0.03030303 0.12121212
## 2 0.16161616 0.32323232 0.32323232
chisq.test(dados_videos$q36, dados_videos$q3)
## Warning in chisq.test(dados_videos$q36, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q36 and dados_videos$q3
## X-squared = 4.4066, df = 2, p-value = 0.1104
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q37,q3))
table
## q3
## q37 1 2 3
## 1 8 22 31
## 2 12 13 13
prop.table(table)
## q3
## q37 1 2 3
## 1 0.08080808 0.22222222 0.31313131
## 2 0.12121212 0.13131313 0.13131313
chisq.test(dados_videos$q37, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q37 and dados_videos$q3
## X-squared = 5.4274, df = 2, p-value = 0.06629
chisq.posthoc.test(table)
table<-with(dados_videos,table(q38,q3))
table
## q3
## q38 1 2 3
## 1 4 11 20
## 2 16 24 24
prop.table(table)
## q3
## q38 1 2 3
## 1 0.04040404 0.11111111 0.20202020
## 2 0.16161616 0.24242424 0.24242424
chisq.test(dados_videos$q38, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q38 and dados_videos$q3
## X-squared = 4.2631, df = 2, p-value = 0.1187
chisq.posthoc.test(table)
table<-with(dados_videos,table(q39,q3))
table
## q3
## q39 1 2 3
## 1 0 4 4
## 2 20 31 40
prop.table(table)
## q3
## q39 1 2 3
## 1 0.00000000 0.04040404 0.04040404
## 2 0.20202020 0.31313131 0.40404040
chisq.test(dados_videos$q39, dados_videos$q3)
## Warning in chisq.test(dados_videos$q39, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q39 and dados_videos$q3
## X-squared = 2.3468, df = 2, p-value = 0.3093
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q40,q3))
table
## q3
## q40 1 2 3
## 1 0 0 6
## 2 20 35 38
prop.table(table)
## q3
## q40 1 2 3
## 1 0.00000000 0.00000000 0.06060606
## 2 0.20202020 0.35353535 0.38383838
chisq.test(dados_videos$q40, dados_videos$q3)
## Warning in chisq.test(dados_videos$q40, dados_videos$q3): Chi-squared
## approximation may be incorrect
##
## Pearson's Chi-squared test
##
## data: dados_videos$q40 and dados_videos$q3
## X-squared = 7.9839, df = 2, p-value = 0.01846
chisq.posthoc.test(table)
## Warning in chisq.test(x, ...): Chi-squared approximation may be incorrect
table<-with(dados_videos,table(q41,q3))
table
## q3
## q41 1 2 3
## 1 7 8 22
## 2 13 27 22
prop.table(table)
## q3
## q41 1 2 3
## 1 0.07070707 0.08080808 0.22222222
## 2 0.13131313 0.27272727 0.22222222
chisq.test(dados_videos$q41, dados_videos$q3)
##
## Pearson's Chi-squared test
##
## data: dados_videos$q41 and dados_videos$q3
## X-squared = 6.1963, df = 2, p-value = 0.04513
chisq.posthoc.test(table)